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Sample GSM5908210

Query DataSets for GSM5908210

Status

Public on Feb 19, 2025

Title

control 7 [LP 7]

Sample type

SRA

Source name

control

Organism

Homo sapiens

Characteristics

ethnicity: chinese
subject status: healthy volunteer
tissue type: tissue next to the bresat fibroadenoma
molecule type: small RNA

Treatment protocol

The normal tissue of volunteers was taken from the tissue next to the their fibroadenoma during breast fibormectomy.The GLM tissue was taken from lesion excision after pathological diagnosis is granulomatous mastitis.

Extracted molecule

total RNA

Extraction protocol

Breast tissue were removed,and RNA was harvested using Trizol reagent.Prep Kit for Illumina (NEB, USA)was used with 3 ug of total RNA for the construction of sequencing libraries.
small RNA libraries were prepared for sequencing using standard Illumina protocols

Library strategy

miRNA-Seq

Library source

transcriptomic

Library selection

size fractionation

Instrument model

Illumina NovaSeq 6000

Data processing

Poly-N, adapter and low-quality were removed by in-house perl scripts ，Quality control analysis was performed by ng_qc.
Clean reads were aligned to the mus musculus ensembl 92 using bowtie (Langmead et al.,2009). bowtie was run with ‘-v 0 -k 1’, other parameters were set as default.
Processed reads of length at 18 to 35 nt for animals or 18-30 nt for plants were then mapped to their reference genome and analyzed using the bowtie package (no mismatch). To identify conserved miRNAs, the predicted miRNA hairpins were compared against miRNA precursor sequences from miRBase22.0 (Friedlander et al., 2011) using mirDeep2 and srna-tools-cli were used to obtain the potential miRNA and draw the secondary structures. MirDeep2's quantifier.pl were used to obtain the miRNA counts, and custom scripts were used to obtain base bias on the first position of identified miRNA with certain length and on each position of all identified miRNA respectively.
The characteristics of hairpin structure of miRNA precursor can be used to predict novel miRNA. The available software miREvo (Wen et al., 2012) and mirdeep2 (Friedlander et al., 2011) were integrated to predict novel miRNA through exploring the secondary structure, the Dicer cleavage site and the minimum free energy of the small RNA reads unannotated in the former steps. At the same time, MirDeep2's quantifier.pl were used to obtain the miRNA counts, and custom scripts were used to obtain base bias on the first position of identified miRNA with certain length and on each position of all identified miRNA respectively.
Genome_build: homo_sapiens_Ensembl_97
Supplementary_files_format_and_content: tab-delimited text files include TPM values for each Sample

Submission date

Feb 21, 2022

Last update date

Feb 19, 2025

Contact name

ling jie

E-mail(s)

l811573403@126.com

Phone

13687357643

Organization name

Hunan university of Chinese medicine